000			02676nam a22003498i 4500
001			CR9780511781452
003			UkCbUP
005			20200124160329.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			100519s2010||||enk o ||1 0|eng|d
020			_a9780511781452 (ebook)
020			_z9780521884426 (hardback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aRC267 _b.C75 2010
082	0	0	_a362.196/994 _222
100	1		_aCristini, Vittorio, _d1970- _eauthor.
245	1	0	_aMultiscale modeling of cancer : _ban integrated experimental and mathematical modeling approach / _cVittorio Cristini, John Lowengrub.
264		1	_aCambridge : _bCambridge University Press, _c2010.
300			_a1 online resource (xix, 278 pages) : _bdigital, PDF file(s).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
500			_aTitle from publisher's bibliographic system (viewed on 05 Oct 2015).
505	0		_aPart I. Theory: 1. Introduction; 2. Biological background; 3. Continuum tumor modeling: single phase; 4. Analysis and calibration of single-phase continuum tumor models; 5. Continuum tumor modeling: multiphase; 6. Discrete cell modeling; 7. Hybrid continuum -- discrete models; 8. Numerical schemes -- Part II. Applications: 9. Continuum tumor modeling: a multidisciplinary approach; 10. Agent-based cell modeling: application to breast cancer.
520			_aMathematical modeling, analysis and simulation are set to play crucial roles in explaining tumor behavior, and the uncontrolled growth of cancer cells over multiple time and spatial scales. This book, the first to integrate state-of-the-art numerical techniques with experimental data, provides an in-depth assessment of tumor cell modeling at multiple scales. The first part of the text presents a detailed biological background with an examination of single-phase and multi-phase continuum tumor modeling, discrete cell modeling, and hybrid continuum-discrete modeling. In the final two chapters, the authors guide the reader through problem-based illustrations and case studies of brain and breast cancer, to demonstrate the future potential of modeling in cancer research. This book has wide interdisciplinary appeal and is a valuable resource for mathematical biologists, biomedical engineers and clinical cancer research communities wishing to understand this emerging field.
650		0	_aCancer _xResearch _xMathematical models.
650		0	_aMultiscale modeling.
700	1		_aLowengrub, John, _eauthor.
776	0	8	_iPrint version: _z9780521884426
856	4	0	_uhttps://doi.org/10.1017/CBO9780511781452
999			_c522359 _d522357